machine-writing

Jhave and Scott Rettberg explore the bright side of AI, the revolutionary advancements in creativity and medicine, while trying not to be consumed by the crushing dark side, the "precarious potential for extinction."

Marino and Berry discuss their engagement in weekly conversations about the nature of "code, of ELIZA, its descendants" and how each of these programs have circulated within our critical code culture, along with other "contemporary conversation agents like Siri and ALEXA and, of course, ChatGPT."

Off center, wayward, slightly off path.... Rettberg and Luers discuss their longrunning encounters with writers, artists, computational film makers and other multidisciplinary "people who come to the electronic literature community, and it’s not only writers, but also artists, visual artists, and you find everyone has a similar kind of wayward path."

Like so many generic literary reconstructions, comics are now being transformed into information -- a process that, for postdoctoral scholar Ilan Manouach, is concomitant with the expansion of tools and services in the field of generative AI. Like so many AI emergences (and emergencies), this one poses important challenges to the comics industry and the careers of comics professionals.

Can ChatGPT or other Chatbot interfaces really write anything better than a feeble imitation of postmodern cut-up techniques? Polina and James Mackay think so, and they offer some reasons for holding onto a human, guiding intelligence in the writing process.

With this brief look at Large Language Model surrealism, Nick Montfort locates and identifies "the id of the internet, of publishing, of podcasting."

Scott Rettberg, director of the Center for Digital Narrative (CDN), in conversation with Nick Monfort, who is leading the CDN's Computational Narrative System's research node.

Daniel Punday reviews Andrew Klobucar’s edited collection of essays, The Community and the Algorithm: A Digital Interactive Poetics.

Multimodal AI trained on YouTube-TikTok-Netflix (object-segmented and identified audio-video-speech) and public domain science data (that exceeds the spectrum of human sensorial field) will be grounded in a world that is in some ways vaster than that experienced by a single human neurophysiology.

Drawing on the media theory of Bernard Stiegler, this riPOSTe to recent ebr essays by Heckman, Cayley and Pold considers the implications of automation for knowledge - both its loss among humans, and its acquistion by AI.